The United States and other advanced nations are stepping up their efforts to combat corruption in poorer, less developed nations by publicizing the corruption and by punishing their own companies when they engage in it. The U.S. Congress added a bipartisan amendment to pending financial reform legislation, requiring oil, gas, and mining companies to disclose every payment they make to foreign governments, according to a recent report in The Economist.

But can such efforts stem the tide? My own analysis suggests that before we can deal with systemic corruption we must first come to grips with the fact that it doesn’t occur in a vacuum — it is a symptom of deeply rooted economic and social maladies.

Source: Map from The Economist, data from Transparency International.

The map above shows how the nations of the world stack up on Transparency International’s 2010 Corruption Perception Index or CPI, which tracks government bribes, kickbacks, embezzlement, and other forms of public corruption. Topping the list as the world’s least corrupt nation is Denmark, followed by New Zealand, Singapore, Finland, Sweden, and Canada. The United States ranks 22nd. The BRIC nations – Brazil, Russia, India, and China – rank in the bottom third of the CPI, even though they are among the fastest-growing nations in the world. Countries like Angola, Somalia, Afghanistan, and Iraq are at the very bottom.

To get a better handle on all of this, my colleague Charlotta Mellander and I compared how a nation’s rank on the corruption index compares to its standing on a series of other standard measures — economic development (economic output per capita), the transition to a more highly skilled knowledge economy (human capital levels and the creative class share of the workforce), social tolerance (as measured by Gallup World Poll surveys which track attitudes to gays and ethnic and racial minorities), and the overall level of happiness or life satisfaction (also from Gallup surveys). Note that the CPI ranks countries in reverse order; the higher its score, the less corrupt the country. As always, we caution readers not to make too much of these findings. Our analysis can only identify relationships among variables and in no way implies causation.

The chart above summarizes the key results of our analysis. Generally speaking, the associations we found between corruption and economic and social development are quite striking.

Corruption and Economic Development: Corruption is closely associated with the overall level of economic development: The richer the country, the less corrupt it tends to be (the correlation coefficient between CPI and GDP per capita is .81). The above chart shows this graphically, with wealthier, more advanced nations clustered at the top, and poorer, less developed nations clustered at the bottom.

Corruption and the Creative Class: Corruption is lower in knowledge-based economies. The CPI is highly correlated with human capital (.58) and even more so with the creative class share (.69). The chart above graphs the association between the CPI and the creative class.

Corruption and Social Tolerance: Corrupt nations also tend to be intolerant places. The CPI is correlated with attitudes toward racial and ethnic minorities (.48) and even more so with attitudes toward gays and lesbians (.74), which the political sociologist Ronald Inglehart of the University of Michigan notes is the last frontier of intolerance across the nations of the world. The above chart shows the relationship between CPI rankings and attitudes toward gays and lesbians.

Corruption and Happiness: Corrupt nations tend to have low levels of happiness and life satisfaction. The CPI is highly correlated with overall life satisfaction (.67). The chart above shows the relationship between the two.

It is much easier to condemn international corruption than it is to overcome it. My own analysis suggests that penalizing companies that pay bribes is to treat one symptom while failing to diagnose, let alone attempt to cure, the underlying disease. Corruption is a fact of economic development. It is endemic not just in the poorest and least functional of nations, but even in the fast-growing (but still comparatively less-developed) BRIC. Corrupt nations have more traditional economic structures, based on resource extraction or manufacturing; they have not yet made the transition to highly skilled knowledge economies. Corrupt nations are more likely to be intolerant; their citizens not only must endure lower material living standards but lower levels of happiness and life satisfaction.

If we really want to combat corruption we must deal with the broader and much harder challenges of economic development. When less developed nations begin to leverage their knowledge, skills, and human capital to raise their levels of economic output, then the battle is already won.

Here’s the longer, unedited version of my column published in today’s The Daily Beast – It Wasn’t About the Economy, Stupid.

The conventional wisdom among pundits, pollsters, and political analysts is that the Republican victory in the midterms represents a referendum on – and a stunning of repudiation of – the Obama administration’s stewardship of the economy. “U.S. registered voters choose economic conditions by nearly a 2-to-1 margin over any of four other key election issues as the most important to their vote for Congress,” according to a Gallup organization analysis, a result that held “across all partisan groups.”

But the geographic patterns of Tuesday’s historic election results reveal a curious paradox. While the economy was clearly the voters’ number one concern, economic conditions alone cannot explain why they cast their ballots as they did. A Wall Street Journal analysis of House races found that Democrats held onto their seats in congressional districts that were feeling the recession the worst. “Of the 25 congressional districts hit hardest by the recession—measured by joblessness, poverty rates, and housing prices—16 are currently represented by Democrats. Fourteen of them won re-election despite the Republican tide.”

Economic factors did not drive state-wide races for Senate or governor either. Democrats, for instance, held onto governorships in the blue states of New York, Massachusetts, and Maryland, and they won a victory in California even though it has taken a tremendous economic hit. Despite the massive Republican pickup in the House and smaller gains in the Senate and governors races, the American electoral map continues to reflect its long-held red versus blue shading.

Columbia University’s Andrew Gelman’s influential book Red State, Blue State, Rich State, Poor State sheds light on this conundrum. Rich voters trend Republican, Gelman and his colleagues found, while rich states trend Democratic. My own earlier analysis of polling data suggested that short-term economic factors like the unemployment rate or changes in housing values provided little explanation of state favorites for Senate or governor, while more deep-seated structural factors like income, social class, attitudes toward religion, and openness toward immigrants as well as gays and lesbians were more likely to hold sway.

With the help of my colleague Charlotta Mellander, I took a close look at factors associated with the recession’s impact – like the change in unemployment and in housing prices since the onset of the crisis — that might have influenced voters. We also looked at income and several other structural variables. In The Emerging Democratic Majority, John Judis and Ruy Teixeira argued that Democrats have gained an advantage by adding the wealthier knowledge workers who cluster in urban centers to their historic base among poorer populations and minority groups. On the red side of the divide, blue-collar working class voters have been shifting into the Republican column. Taking this into account, we examined the relations of work and class and partisan choice. Following Ronald Inglehart’s lead, we also looked at the relations between religious values, tolerance, and political preferences. Confining our analysis to state-wide Senate and gubernatorial races, we conducted a basic correlation analysis and compared the results for the current midterm. We also compared the midterm pattern to the state-by-state vote for Obama and McCain in the 2008 presidential race.  As always, we caution readers not to make too much of these findings. The size of the sample is small, and our analysis can only identify relationships among variables, and in no way implies causation. Still, a number of very interesting patterns emerge.

Despite all the hubbub about the economy, we found no evidence at all that short-term economic factors – unemployment and housing prices – significantly shaped state-wide voting patterns for either party. This is not to say that short-term economic factors did not matter at the margin: Clearly, election returns and exit polls showed that many individuals shifted their 2008 Democratic vote to a Republican one in the midterms. But, at the state level, deeper-seated factors remained by far the dominant factor.

Income and class remain important, but less so than in the ‘08 presidential race. Higher-income states went for Obama, while lower-income states went for McCain. This trend continued to hold for Senate races, with higher-income states voting Democrat and lower-incomes states trending Republican, but not for gubernatorial races.

Class also continues to play a role, though its relation was less evident than it was in ‘08.  Obama took states where knowledge workers and the creative class – which makes up roughly  a third of the workforce and includes workers in science and technology; business and management; law; arts, culture, media, and entertainment; health care and education – comprise a larger share of the workforce, while McCain took blue-collar working class states. The creative class was more split in the midterms, and significant segments of it shifted from Obama and the Democrats to the Republicans. While a considerable change from ‘08, it is not surprising, as many creative class voters tend to be independent and more candidate-centered. While the correlation between creative class states and Democrats remained positive, it was not statistically significant. Blue-collar working class states were positively associated with Republican Senate votes and negatively associated with votes for Senate Democrats.

Religious orientation remains a key pivot point in America’s cultural and political divide.  In 2008, more religious states went for McCain and less religious states went for Obama. This pattern continues to hold for the Senate, though not for governors’ races. Religion is positively associated with both Republican votes for Senate and negatively associated with Democrat votes for Senate. (Our religion variable is from Gallup polls that ask individuals if religion is an important part of their everyday life.)

From Tom Tancredo in Colorado to Carl Paladino in New York, we’re constantly reminded that immigration and gay rights remain significant wedge issues in American politics. (We used the percentage of immigrants and gays and lesbians in states as proxy measures for openness). Salient in 2008, openness toward gays and lesbians and toward immigrants were again among the most important factors in state partisan patterns. States with higher percentages of gays and lesbians and higher percentages of immigrants went for Obama in 2008 while those with lower percentages went for McCain, and these trends also continue to hold. Immigrants appear to have a more substantial relation with votes in Democratic states, while gay and lesbians have a more noticeable association with Republican states. States with larger percentages of immigrants were more likely to vote Democratic in both Senate and governor races. The percentage of immigrants was negatively associated with Republican votes for Senate but not significantly associated with Republican votes for governor.  The percentage of gay and lesbian residents in a state was negatively associated with Republican votes for both Senate and governor, and it was positively associated with the Democratic votes for Senate but not significantly associated with Democratic votes for governor

But, the strongest factor of all in our analysis was the red-blue pattern itself. States that voted for Obama in ‘08 tended to elect Democrats to Senate and governor, while those that went for McCain again went for Republicans. The correlations were significant for both Senate and governor races across both parties, though they were about twice as powerful for Senate races.

The upshot of this could not be clearer. We witnessed no massive realigning of the electoral map; instead, America remains divided along the same political, cultural, and economic axes. Richer states are still more likely to be Democratic and poorer ones Republican. But it’s about more than just money. The creative class might have split its vote to some degree, but working class states continue to trend red, while states with higher percentages of immigrants and especially gays and lesbians continue to tack Democratic.

Of course economic conditions do play a role in elections and this one is no exception. Obama benefited strongly from the support of the creative class in 2008; economic conditions have considerably tempered their enthusiasm this time around. And “throw the bums out” inevitably takes a greater toll on the party in power.

But a discernible political pattern remains, one that is etched in a deep class divide that is rooted in the very structure of our economy. It’s not just that more educated, higher income, knowledge workers prefer to live in denser cities and metro areas on the coasts. The logic of an idea-driven economy generates innovation and productivity by concentrating them there. But just as the economy benefits from the concentration of human capital and the creative class in tighter, spikier geographic locations, our political system penalizes it, as evidenced by the big swaths of red in the less densely populated states and the smaller specks of blue on America’s new electoral map.

And this political reality handicaps the nation’s ability to address the very serious economic problems it faces. In previous periods of economic crisis and transformation, like the Long Depression of the late 19th century and the Great Depression of the 1930s, America benefited from the “critical realignments” that were long ago identified by Walter Dean Burnham, which recast the electorate to create more stable governing and policy coalitions. These political realignments shift the power balance between the parties and, in doing so, provide the political underpinnings for the major changes in public policy that are needed to help the nation adjust to structural economic change.

Though our economy is currently in the midst of a similar great reset today, our politics reflect what Burnham called an “unstable equilibrium.” In fact, the overlay of class and geographic divides, combined with Washington’s inability to get much done, creates an especially volatile backlash-gridlock-backlash partisan cycle. Democratic anger at Bush motivated massive voter enthusiasm in the ‘06 and ‘08 cycles among Democrat-leaning groups. The same kind of mobilization was apparent not just in the Tea Party but in Republican-leaning groups this cycle.  According to a November 2 Gallup poll, 63 percent of Republicans surveyed reported that they were more enthusiastic than usual about voting — an all-time high. Americans are most enthusiastic about voting when they feel the least empowered – it is hardly an inspiring picture.  This backlash cycle is chronically unstable. No sooner is a new administration or a new congressional majority in place than anger begins to mount on the other side and the cycle begins again. To match our unstable economy, we have an unstable political system.

The consequences of this backlash-gridlock cycle extend far beyond politics, paralyzing America’s ability to deal with the deep and fundamental economic issues it faces. Just when the United States needs bold, forward-looking leadership which can develop broad efforts to renew the economy, upgrade jobs, spur innovations, and address mounting inequality, it is stymied by a volatile political system propelled by anger and backlash, leaving it with gridlock and inertia.

They keep rolling in (h/t Chris Hardwicke). And they continue to reinforce the depth of the class divide.

Social media is redefining the landscape of everything we do, from the way we connect to family and friends, how brands and celebrities capture attention, to the way business and journalism function. Hundreds of millions of people across the world use social networks like Facebook, Twitter, and LinkedIn. If any technology promised to shatter the constraint of geography, overcome distance, and flatten the world, social media would be it.

But a quick look at the map below, from the NetProspex 2010 Social Business Report, shows this is not the case at all, certainly not for the United States.

The map shows the 50 leading social media cities in the United States. It is based on data collected by NetProspex on social media adoption and used by more than two million business professionals.

The level of geographic concentration is pronounced, though the leading social media metros are not surprising. San Francisco and San Jose, Silicon Valley, top the list, with New York City, Austin, Boston, Seattle, Denver, Salt Lake City, L.A., and Atlanta rounding out the top 10.

But what are the characteristics of America’s leading social media centers? What factors are associated with its greater adoption and use in certain kinds of metros?

With the steady statistical hand of Charlotta Mellander, I decided to take a look at a range of factors that might be associated with geographic centers of social media. We examined key factors like economic development and income; clusters of high-tech industry; the human capital; creative class vs. working class job structures; the presence of artists, musicians, designers, and other artistic creatives; and openness to diversity and tolerance for immigrants and gays and lesbians (see the note on sources at the end of this post). We ran a basic correlation analysis and generated a series of scattergraphs plotting social media centers against these factors.

The chart above summarizes the key findings of our analysis. These are preliminary, exploratory analyses that simply point to associations between variables. We don’t make any claims about the direction of causality, and we acknowledge that intervening variables may come into play. So what do we find?

Economic Development and Income: It stands to reason that the adoption of the use of social media at the city level would rise alongside local incomes and the overall level of economic development. And that is what we find. Social media is associated with both economic output and income. The correlations for each are substantial (in the range of .6 and .7).

High-Tech Industry and Innovation: It also stands to reason that social media would be more commonly used in places with higher levels of high-tech industry and higher rates of innovation. And again that is what we find. The correlation between social media centers and concentrations of high-tech industry is about the same as for economic development (ranging from .6 to .7). While social media at the city level is correlated with the rate of innovation, measured as patents, the correlation is more modest (about .4).

Human Capital: Social media use is also associated with higher levels of human capital, measured as the share of adults with a bachelor’s degree or more education (with correlations in the range of .55 to .6).

Creative Class vs. Working Class: The class structure of the economy also seems to play a substantial role. Social media centers are also associated with higher concentrations of creative class jobs in fields like science and technology; business, management, and finance; arts, culture, and entertainment; and health care and education (with correlations in the range of .55). Social media centers are also significantly associated with artistic and cultural creatives specifically (with correlations ranging from .525 to more than .7). On the other hand, places with a larger blue-collar working class labor force tend to have lower concentrations of social media (with correlations ranging from .-3 to nearly -.4).

Openness to Diversity: I’ve long argued that openness to diversity – measured either as openness to foreign-born people or to gay and lesbian populations – reflects a place that is open to new ideas generally and enables outsiders to mobilize resources efficiently around these new ideas and firms. Open places benefit from low barriers to entry to talented people, and benefit from their ability to capture a greater flow of creative, innovative, and ambitious people. Both measures are closely associated with social media centers. Social media centers are closely associated both with the Gay Index – a measure of the proportion of gays and lesbians in a metro area (with correlations ranging from .62 to nearly .7) – and the share of foreign-born people in a metro (with correlations of .6 and higher).

While social media allows us to connect instantaneously to people all over the globe, the geography of its professional use in the United States is concentrated. The leading social media metros in the U.S. are richer, more technologically advanced, have higher levels of education and higher levels of the creative class, and are more open to diversity of all sorts. The geography of social media thus both reflects and reinforces the increasingly uneven and spiky nature of America’s economic landscape.

Notes on Data and Sources: Social media metros is from the NetProspex 2010 Social Business Report based on data on social media use by more than two million business professionals. The variable is logged in the scattergraphs above.

Economic Output is gross domestic product per capita and is from the Bureau of Economic Analysis. High-Tech is based on the Milken Institute’s Techpole measure – regional high-tech intensity compared to national high-tech intensity updated with current data. Innovation is patents per capita and is from the U.S. Patent and Trademark Office.

Creative class includes the share of workers in science and technology; business, management, and finance; arts, culture, media, and entertainment; and health care and education. Working class includes the share of blue-collar workers in production occupations, maintenance, construction, and transportation. Bohemian Index is the share of adults in artistic and culturally creative occupations. These variables are from the Bureau of Labor Statistics.

Human capital is the share of adults  with a bachelor’s degree and above. Gay Index is the share of adults that are gay and lesbian and is based on research developed by Gary Gates and his collaborators. Foreign-born is the share of adults who were born outside of the United States. These variables are from the U.S. Census American Community Survey.

With the midterm elections only two weeks away and the Democrats in jeopardy, the prevailing wisdom is that the election will be a referendum on the Obama administration’s stewardship of the economy. A large fraction of 2008 Obama voters now cite the economy and jobs as the key reason they will vote Republican this year, according to an October 17 AP poll. “The president must zero in on the economy if he wants to help himself and his party,” writes Eleanor Clift. The basic notion here, promulgated by pundits and political analysts, is that the current political environment turns on the vagaries of the economy. This amounts to a cyclical theory of American politics. And, in fact, several decades ago, the political scientist Douglas Hibbs advanced his seminal theory of the “political business cycle” which argues that economic movements have a sizable effect on American elections.

But another line of thinking suggests that American politics turns on deeper structural changes in economy and society. In the influential Red State, Blue State, Rich State, Poor State, Columbia University’s Andrew Gelman and his colleagues uncovered a paradox that both confirms and defies the conventional wisdom about American elections. While rich voters trend Republican, rich states trend Democratic, he found. The opposite holds as well. Though poor and minority voters overwhelmingly pull the lever for Democrats, poor states consistently end up in the Republican column. A second version of the structural approach comes from John Judis and Ruy Teixeira, who argue in The Emerging Democratic Majority that the rise of the post-industrial economy has tilted the playing field toward Democrats who gain advantage in wealthier urban “ideopolises” while holding onto the votes of the poor and minorities. A third perspective comes from Ronald Inglehart of the University of Michigan, whose detailed World Values Surveys identify a shift in political culture from the more traditional, religious, and materialist orientations of the industrial age to post-materialist values of self-expression, openness to diversity, secularism, and broad public goods like concern for the environment.

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This juxtaposition thus mirrors the debate over the economy: Will shorter-term cyclical factors determine the outcomes of the mid-terms or are deeper structural factors at play?

With the help of my colleague Charlotta Mellander, I decided to take an empirical look at this question. On the one hand, we considered a series of key cyclical variables such as the unemployment rate and its change since the economic crisis began, and also housing prices and their change since the bubble burst. And, on the other hand, we considered key structural factors, such as income a la Gelman, post-industrialism a la Judis and Teixeira (measuring the prevalence of creative class jobs versus working class jobs), and post-materialist political values a la Inglehart, including the prevalence of religion and openness to both immigrants and gays and lesbians. We confined our analysis to the state level, using pooled polling data for both Senate and governor races across the country, which we drew from Nate Silver’s FiveThirtyEight election forecasts at The New York Times. We conducted a basic correlation analysis and compare the results for the current midterm to those for Obama and McCain in the 2008 presidential race. (The graph below summarizes the key findings). This kind of analysis can only point to associations between factors and does not identify any causal pattern, and of course other factors may come into play. Polling data covers a much smaller number of observations than election returns and suffers from other problems. For these reasons, we caution against drawing overly broad conclusions from this exercise. Still, the patterns it points to are quite interesting.

Despite all the “it’s the economy, stupid” hub-bub among the chattering classes, our analysis finds little empirical support for the cyclical view. There was no statistical association at all between the share of voters leaning Democrat or Republican for either Senate and governor races and our key cyclical factors – the unemployment rate, the change in the unemployment rate, housing values, or change in housing values. This is not to say that these factors do not matter at the margin, as polling data clearly tell us that  many individuals are shifting their 2008 Democratic vote to a Republican vote in these midterms.

But it’s structural factors on which this election is much more likely to turn. We find significant statistical associations between most of the structural variables in our analysis and the share of voters leaning Democrat or Republican in both Senate and governor races, as detailed below.

Income: Higher income states went for Obama in 2008 while lower income states went for McCain. The trend continues, even in light of the ongoing economic malaise. Income is positively associated with Democratic share for Senate (.4) and governor (.36) races. And it is negatively associated with Republican share for Senate (-.54) and governor races (-.38). These associations have weakened more on the Democratic side (.52 for Obama) than for the Republicans (.-51 for McCain).

Class: Class played a role in the 2008 presidential election and it continues to do so in the midterms. Creative class states went for Obama in 2008 and working class states went for McCain, and this holds up for the midterms as well. The creative class is positively associated with Democratic share in both Senate (.34) and governor (.36) races, and negatively associated with Republican share in each (-.38 for Senate and -.52 for governor). These associations have again weakened more for the Democrats (.52 for Obama) than for the GOP (-.46 for McCain) in 2008.

Working class states voted overwhelmingly for McCain in 2008 and this remains the pattern today. The working class is positively associated with both Republican share for governor (.46) and Senate (.48) and negatively associated with Democrat share for both (-.34 for governor and -.38 for Senate). The results are slightly weaker than for the 2008 contest (.64 for McCain, -.64 for Obama). While many creative class members vote Republican and many working class members vote for Democrats, the state-level patterns show the continuing salience of class for American politics.

Post-materialism: The shift from traditional, religious to more secular values is a hallmark of post-materialist political culture. In 2008, more religious states went for McCain (.63) and less religious states went for Obama (-.59), and this patterns continues to hold. (Our religion variable is from Gallup polls which ask individuals if religion is an important part of their everyday life.) Religion is positively associated with both Republican share for governor (.37) and Senate (.55), and negatively associated with Democrat share for Senate (-.46), though the correlation for Democrat share for Senate (-.22) is not significant. The patterns are also weaker than in the 2008 presidential election, especially on the Democratic side (.63 for McCain and -.59 for Obama).

From Tom Tancredo in Colorado to Carl Palladino in New York, we’re constantly reminded that immigration and gay rights remain significant wedge issues in American politics. We employ openness to immigrants and gays and lesbians (based on share of adult population) as proxy measures for opennesss – another key marker of post-materialism. States with higher percentages of gays and lesbians and higher percentages of immigrants went for Obama in 2008 while those with lower percentages went for McCain, and these trends also continue to hold. The percentage of foreign-born residents is positively associated with Democratic share in both Senate (.38) and governor (.36) races, and negatively associated with the Republican share in each (-.27 governor, -.5 Senate). These associations have weakened more on the Democratic side (.52 for Obama) than for the Republicans (.-51 for McCain).

The percentage of gay and lesbian residents is positively associated with the Democratic share in both Senate (.58) and gubernatorial (.47) races, and negatively associated with Republican share (-.68 for Senate, -.46 for governor). These associations are comparable for 2008 (.57 for Obama, -.57 for McCain) and among the strongest of any in our analysis. Clearly, openness remains a key factor in state-level politics.

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Despite all the attention that has been paid to the effect of current economic conditions on the upcoming midterm elections, structural factors remain the central axis upon which American politics turns. Yes, richer states are more likely to be Democratic and poorer ones Republican. But it’s more than money. States that have transitioned to more knowledge-driven creative class economies are more likely to be blue, while working class states are more likely to be red, echoing former Republican Congressman Tom Davis’s blunt statement: “Economic development works” – meaning that it tends to turn places to more open-minded, liberal bastions. In line with this and with Inglehart’s notion of the shift toward post-materialist values and cultures, states with higher percentages of immigrants and especially gays and lesbians continue to tack Democratic.

Cyclical factors do play a role in elections and this one is no exception. If Obama benefited from the enthusiasm of creative class voters in 2008, economic conditions have undoubtedly tempered this somewhat this time around. Gays and lesbians have been vocally disappointed with Obama’s failure to act on Don’t Ask, Don’t Tell — a frustration that may well turn out to be discernible in lower turnouts. And, of course, anti-incumbent sentiment is at an all-time high. And “throw the bums out” inevitably takes a greater toll on the party in power.

American politics is periodically recast by “critical realignments” long ago identified by Walter Dean Burnham, like the elections of 1896 and 1932. These political realignments shift the power balance between the parties and, in doing so, provide the political underpinnings for major public policy change which helps the nation better adjust to structural  economic change. Though our economy is currently in the midst of a similar great reset today, whether or not our politics realigns remains an open question.

The connection between creative class states and the Democrats, and working class states with the Republicans is a clear break from the old pattern of the New Deal and post World War II. But it’s equally clear that both parties are constrained by their connections to long-held special interests. By paying excessive deference to the social conservatism and extreme anti-statism of its right fringe, the Republicans are unable to attract the creative class broadly, even though many of its members are drawn to its individualist ethos and fiscal conservatism. Democrats, meanwhile, remain captive to the housing-finance-auto industrial complex which literally defined the old order. As the Cato Institute’s Brink Lindsey quipped some years ago, “Here, in the first decade of the 21st century, the rival ideologies of left and right are both pining for the ’50s. The only difference is that liberals want to work there, while conservatives want to go home there.” A sustained political realignment will only come about when one or the other of the two major parties is able to shuck off the interests that tie it to the past and develop an agenda that is in line with the future.

Unless and until that happens, the United States is likely to remain stalled at its current impasse, lurching between economic and political cycles, while failing to address the deep structural challenges it faces – and unable to develop the much-needed reforms, new economic policies, and broad infrastructure investments required for a new round of sustained prosperity.

Here’s the long version of my column published in today’s The Globe and Mail.

Canadians often point to the angry red versus blue divide that is such a hallmark of American politics, with higher-income, more economically advanced places voting Democratic and less-affluent, more working class locales trending Republican, as a problem that Canada has risen above. But this same kind of cleavage has become increasingly apparent in Canada – glaringly so in Toronto’s upcoming mayoral election.

The most recent Nanos poll shows Rob Ford leading in Etobicoke, North York, and Scarborough, while George Smitherman leads in old Toronto. The conventional wisdom is that this is a product of amalgamation and the rise of the mega-city, which brought two distinct constituencies into one political jurisdiction in 1998. But it runs far deeper than that.

My Martin Prosperity Institute research team overlaid a map of the strongholds of the various mayoral candidates with another showing where creative, service, and blue-collar workers work. The division isn’t just urban-suburban.  Toronto’s economic and political geography takes the shape of a “T” that divides the city on an east and west as well as a north to south axis.  Higher-paying, higher-skill, creative class jobs – in fields spanning science and technology; business and management; arts, culture, and entertainment; health care and education – are concentrated along subway routes radiating out of the downtown core of the city in both directions. Lower-skill, lower-wage jobs are concentrated at the periphery of this T in both the core and more outlying areas. There are only a handful of districts left in the city where working class jobs predominate. One of them, up in the far left hand corner of the map, is Ford’s. Smitherman’s former riding and Pantalone’s ward are right smack in the middle of the T.

In the United States, that political divide is also a jurisdictional divide – pitting city against suburb. Joel Kotkin, who I have debated many times, has written about the increasing Balkanization of California along competing lines of class and occupation, with its affluent clustered along its coast and its farmers and middle class suburbanites concentrated in the state’s interior. The result, he writes, “is two separate…realities: a lucrative one for the wealthy and for government workers, who are largely insulated from economic decline; and a grim one for the private-sector middle and working classes, who are fleeing the state.” He might as well have been writing about Toronto.

But in Toronto it is taking place inside the city itself.  This inconvenient but unavoidable truth runs counter to a deep and long-standing perception: A social and political consensus – shared by NDPers, Liberals, and Conservatives alike – that Toronto, for all its demographic and economic variety, is at bottom “one” cit, and that it is a fair and equitable place. George Smitherman, Rocco Rossi, Joe Pantalone, and even John Tory, despite their differences, all reflect that same consensus — one that has streteched all the way from David Crombie and Mel Lastman to David Miller. The current election campaign shows how frayed that consensus has become. Ford, as Chris Hume wrote some time ago, “has tapped into a deep well of exurban fear and loathing… He personifies anti-urbanism, which makes him a hero.”

There has been considerable discussion in this campaign about whether we should concentrate on building more subways or light rail; much has been made of Ford’s adamant opposition to new bicycle paths. But these discussions ignore the basic fact that transit is bound up with Toronto’s class divide, as MPI research has shown. The members of Toronto’s struggling service and working classes – the ones who need public transit most — are woefully underserved. Forty-five percent of creative class members work within 500 meters of a subway line. Among the service class, that number drops to 31 percent. Buses could pick up some of the slack, but they don’t — they all too often run infrequently and on indirect routes. A five kilometer commute to the central city can take up to 40 minutes. Whether justly or not, Toronto’s working people feel that the city’s government is bloated and elitist and complacent, they believe that it benefits upscale urban dwellers and does not work for them.

Government did not cause Toronto’s (or for that matter, California’s) cleavages — they are the result of a fundamental economic restructuring that has brought enormous boons to some and left others out in the cold. As manufacturing shifts abroad and the technology and knowledge economy burgeons, innovative companies, highly skilled people, and the jobs that employ them have formed dense clusters. It is this very process which drives economic development forward, spurring innovation, generating new entrepreneurial firms, and creating new opportunities. But it also drives up housing values and splits up and sorts people by work and income.

The logic of capitalism is filled with contradictions. Those contradictions create new wealth and simultaneously bring new divisions and new social costs. Toronto, like virtually every other major city in North America, stands at a critical inflection point. Its recent economic success has, in effect, split it right down its middle.

When I first moved to Toronto, I believed we still had a chance to avoid the fraying of the social compact that is eating away at the states. But it has happened here too and it will not go away.

This, it seems to me, is the real subtext of this election, the understory that we have not wanted to acknowledge. Toronto has fallen victim to the same spiky structural forces that are concentrating economic assets and dividing communities across the globe, here in North America and right here in our very own city. We cannot push this under the rug. Regardless of what happens on election day, we must all face up to the fact that we are no longer one Toronto. That is the central challenge that the next mayor and all of us will be dealing with long after this election is past.

Last Friday, my list of America’s Brainiest Cities ran over at The Daily Beast. Boulder topped the list, which comprised a mix of larger knowledge-intensive metros like Washington, D.C., Boston, Silicon Valley, San Francisco, Austin, and Seattle, and college towns like Ithaca, Charlottesville, Madison, Iowa City, and Durham, North Carolina, among others.

The map above, prepared by Zara Matheson of the Martin Prosperity Institute, shows the performance of all U.S. metros on our Brainiest Metros Index developed with my colleague Charlotta Mellander. The index is based on three variables:

• The share of adults 25 years of age and older with a PhD, master’s, or professional degree (from the U.S. Census American Community Survey).
• Computer scientists and mathematicians as a share of all employment.
• Scientists (physical, biological, social) as a share of total metro employment (both from Bureau of Labor Statistics).

The Index weights all three variables equally and covers 339 U.S. metro regions.

Now let’s look quickly at how U.S. metros perform on these three key factors that make up the overall index.

The first chart above maps U.S. metros on the first variable – the share of adults with a PhD, master’s, or professional degree. The blue shaded areas show regions that score highly on this variable. Washington, D.C. is the clear leader among larger metros (those with more than one million people). Greater Boston and the San Francisco Bay area also have considerable concentrations. But the highest-scoring metros are all college towns that are home to large research-intensive universities – Ithaca (Cornell), Boulder (University of Colorado), Corvallis (Oregon State), Charlottesville (University of Virginia), State College (Penn State), Iowa State (University of Iowa), Lawrence (University of Kansas), and Gainesville (University of Florida).

The second map shows U.S. metros on the second variable – computer scientists and mathematicians as a share of total metro employment. California’s Silicon Valley-San Jose rates highly, along with Durham in North Carolina’s Research Triangle, Washington, D.C., Boulder, Boston, Austin, Seattle, and several others.

The third map traces U.S. metros on the third variable – scientists as a share of all metro employment. The high-ranking metros here are almost all significant university towns.

But to what extent is metro “braininess” associated with better rates of economic performance? Human capital is a key driver of economic performance, according to a wide range of economic studies. And the Brainiest Metros Index reflects a small but high-powered subset of human capital. To get at this, we ran a series of correlation analyses and scattergraphs comparing the Brainiest Metro Index to measures of regional economic output, income, and wages; innovation and high-tech industry; housing prices; job and class structures; and even metropolitan happiness and well being. These are preliminary, exploratory analyses that simply point to associations between variables. We don’t make any claims here about the direction of causality, and we acknowledge that intervening variables may come into play.

Brainier metros have better economic outcomes, being closely associated with economic output measured as gross regional product per capita (with a correlation of. 556), regional income (.563), and regional wages (.646). Metro braininess also goes along with higher housing prices, whether measured by the Case-Shiller Index (.449 ) or by Census data on housing values (.358).

Brainier metros also have higher levels of innovation, measured as patents (.571), and have higher levels of high-tech industry (.698).

Brainier metros also reflect broader regional occupational and class structures. They are positively associated with the creative class (.77) and negatively associated with the working class (-.53).

And brainier metros tend to have happier populations. The correlation between the Brainiest Metros Index and Gallup’s measure of metropolitan happiness and well-being is.566.

This poses significant implications for economic development policy, which I pointed out at The Daily Beast:

Though luring new factories and building new stadiums lend themselves to outsize media attention and ostentatious ribbon-cutting ceremonies, the less glamorous work of building up local knowledge assets and leveraging existing university campuses yields far greater and lasting economic gains. Unlike incentive packages and new stadiums, which, despite their price tags of hundreds of millions of dollars, too often turn out to provide benefits that are scant or fleeting, knowledge assets like research universities can’t move; they are rooted in the local economy. These brainy metros not only demonstrate a better approach to stimulating state and local economic development, they are helping to rebuild the US economy as a whole.

A new report from our Martin Prosperity Institute team charts the geography of class in Toronto. The map below shows the deep underlying economic – class - divisions of the city and can also help us understand the current polarized mayor’s race.

The map shows the concentration of three broad classes of work across the city’s census tracts. The kind of work people do is the hallmark of social-economic class and the map shows a city where the dominant classes occupy, literally, two different social, economic, and geographic spaces. This segmented pattern mirrors the same trend identified by earlier research on the worsening residential segmentation of the city highlighted by my University of Toronto colleague David Hulchanski.

Higher-paying, higher-skill creative class jobs – in fields spanning science and technology; business and management; arts, culture, and entertainment; health care and education – are concentrated in a T-shape pattern radiating out of the downtown core of the city. Lower-skill, lower-wage jobs surround the creative class T and are concentrated in more outlying areas. Toronto’s geography reflects a city that has become almost completely post-industrial: There are very, very few districts left in the city where working class jobs are the dominant concentration. But where those jobs are can help us understand the mayor’s race and Toronto’s increasingly class-polarized politics.

The two leading candidates come from completely different economic and geographic worlds. The only working class concentrations in the upper left-hand quadrant of the map are in or very close to Rob Ford’s city council riding. Prior to running for mayor, George Smitherman represented the Toronto Centre Provincial riding, an area that is at the virtual apex of the creative class zone.

Toronto needs to come to grips with its growing class divide, and to develop strategies that can begin to address it if it wants to retain the tolerance, social cohesion, and commitments to social justice which have so long been its hallmarks.

The United States has seen a steady erosion of blue-collar work over the past several decades. We define blue-collar, working class jobs as those which primarily make use of physical skill or manual labor. These occupations include not only factory work or production occupations, but jobs in construction, materials moving, transportation, installation, and repair. Blue-collar, working class jobs currently account for 23 percent of all U.S. employment. Blue-collar occupations and the regions that specialize in this kind of work have seen the highest levels of unemployment and the greatest vulnerability to the economic crisis. The decline of high-paying, blue-collar jobs for lower-skilled workers has caused considerable concern that the U.S. is losing an important source of good, family-supporting jobs, and that the American labor market is becoming more uneven and increasingly split between higher-paying knowledge work and lower-paying routine service work. But what will the geography of blue-collar work look like in the future?

The map above shows the metros with the biggest projected gains in blue-collar work. Not surprisingly, the biggest metros top this list. The biggest gainer is Greater New York which is projected to gain 41,084 working-class jobs followed by Houston (32,249), Chicago (30,482), Los Angeles (28,811), Phoenix (23,957), Atlanta (22,754), Washington, D.C. (21,387), Dallas (19,315), Riverside (16,755), and Las Vegas (14,781).

But job growth is a function of population size; it’s expected that large regions will dominate the list of the biggest job generators. So, the next map plots the projected percentage change in working-class jobs for U.S. metros. The regions with the largest projected working class increases are all in the Sun Belt: Pascagoula, MS (8.2 percent), Naples, FL (8.1 percent), Punta Gorda, FL (7.9 percent), Santa Fe, NM (7.4 percent), Cape Coral, FL (7.4 percent), Farmington, NM (7.4 percent), Jacksonville, NC (7.2 percent), Las Vegas ( 7.1 percent), Grand Junction, CO (7 percent), and St. George, UT (7 percent). The places with the slowest projected growth are mainly traditional manufacturing metros such as Elkhart (.2 percent) and Columbus, IN (1.06 percent), Muskegon, MI (1.16 percent), Oshkosh, WI (1.41 percent), Hickory, NC (.68 percent), and Dalton, GA (.46 percent), among others.

The next map shows the regions that are projected to have the highest share of their workforce doing blue-collar work out to 2018. Elkhart, IN, tops the list with nearly half (48.5 percent) of its workforce in blue-collar jobs – though that is down from 51.3 percent in 2008. It is followed by Dalton, GA (45.9 percent), Morristown, TN (40.9 percent), Houma, LA (40 percent), Decatur, AL (37.6 percent), Fort Smith, AR (36.5 percent), Hickory, NC (35.8 percent), Odessa, TX (35.4 percent), Gainesville, GA (35.3 percent), and Sheboygan, WI (34.3 percent).

The good news is that the U.S. will continue to create relatively high-paying working class jobs. These jobs will continue to provide good livelihoods for the workers fortunate enough to have them. The bad news is that their rate of growth will be sluggish and not nearly enough to provide the amount of good, family-supporting jobs required to undergird a middle class of lower-skilled workers. The harsh reality is that blue-collar, working class jobs in the U.S. are increasing slowly, and they will grow the slowest in traditional manufacturing and industrial regions and communities whose economic and social life has revolved around these jobs. There is little policy-makers can do – aside from declaring a trade war – to bring back large numbers of these high-paying jobs. But they can develop strategies to improve not just the wages but the content of blue-collar work, by engaging workers more fully and seeing them as a source of innovation. And they can help to infuse more creativity and design into manufacturing products, helping to broaden their market and counteract the trend toward declining prices. And policy-makers will have to develop strategies for improving wages and the content of work in other faster-growing segments of the economy, a point I will get to in my next post, which will cover the projected growth of service jobs.

Last Friday, my list of the 20 metros with the fastest-growing jobs was posted over at The Daily Beast. Jobs are the second-biggest issue facing the United States – second only to the economy, according to a recent Gallup poll – and a pending referendum on the Obama administration in the upcoming mid-term elections. As I noted:

The United States has lost an estimated 7.4 million jobs since the onset of the economic crisis. But, the economy is on track to create some 15.3 million new jobs looking out to 2018, according to projections done by the Bureau of Labor Statistics (BLS). And more than 50 million total jobs will come open, as older workers retire and many switch jobs and careers. Total U.S. employment is projected to grow by 10.1 percent over the period, according to the BLS forecast, considerably better than the 7.4 percent growth rate for previous decade (1998-2008), and roughly in line with population growth of 10.7 percent.

But where will the new jobs be located? Which places will grow the most jobs and, conversely, which will see the biggest job losses?

To get at this, my Martin Prosperity Institute (MPI) team applied the detailed employment projections of the BLS to U.S. metro regions. The BLS forecasts job trends across 22 major occupational groups which include more than 822 specific job categories for the decade 2008 through 2018. My MPI team used these BLS national forecasts to generate similar estimates for each of America’s 392 metro regions. Essentially, we used the BLS overall estimations to predict job growth in each region based on its current mix of jobs.

Over the next couple of weeks, I’ll be posting the results of our analysis here. I’ll get us started today with a series of maps and analyses of the metros that stand to gain the most jobs overall.

The map above shows the metros with the biggest projected gains in total employment out to 2018. New York is projected to add 578,974 jobs, the most in the country. It is followed by Los Angeles (405,392), Chicago (344,740), Washington, D.C. (261,465), Atlanta (235,036), Houston (232,001), Philadelphia (202,970), Dallas (203,202), Phoenix (191,210), and Boston (186,457).

But job growth is a function of population size; it’s expected that large regions will dominate the list of the biggest job generators. So, the next map (below) plots the projected percentage change in overall employment for U.S. metros.

Rochester, Minnesota, is the biggest percentage gainer, with projected job growth of 12-plus percent. The major hub cities of the Bos-Wash corridor do well with Greater Washington in second place, Greater New York in 15th, and Boston 19th. The D.C. suburb of Bethesda and Trenton-Ewing – a suburb of both New York and Philadelphia – also number among the top 10. College towns like Charlottesville, VA, Gainesville, FL, Ithaca, NY, Boulder, CO, and Corvallis, OR, which have performed well over the course of the economic crisis, number among the nation’s top 20 projected job gainers.

The biggest projected job losers are mainly older manufacturing communities. Elkhart, Indiana, a region which currently ranks near the top of this list in terms of unemployment, also ranks last in terms of projected job gains, adding just 6,639 total jobs – a 5.4 percent gain. Next is Dalton, GA (5.6 percent), Morristown, TN (7 percent), Visalia, CA (7.3 percent), Columbus, IN (7.7 percent), Decatur, GA (7.7 percent), Cleveland, TN (7.8 percent), Hickory, NC (7.8 percent), Holland, MI (7.8 percent), and Gainesville, GA (7.9 percent).

But what accounts for this growth? We ran correlations for key economic, social, and demographic variables and the percentage change in employment from 2008 and 2018. These are preliminary, exploratory analyses that simply point to associations between variables. We don’t make any claims here about the direction of causality, and we acknowledge that intervening variables may come into play. Several key factors emerge as driving forces in the regional jobs equation.

Size matters, but only to a very slight degree. Population is only very slightly correlated with percentage change in employment (.17).

Characteristics of the labor force and of metro economies matter much more. Human capital is very closely associated with percentage change in metro level employment (.56). The scattergraph above plots the association.

The nature of the economy is also closely associated with metro job growth. The percentage change in metro employment is closely associated with the percentage of the workforce in the creative class (.64).

But it is even more strongly associated with the share of the labor force in blue-collar, working class jobs, where the correlation is high and negative (-.84).

This suggests that the structural forces that are reshaping the U.S. economy from an industrial to a more idea, knowledge, and human capital driven post-industrial economic system will continue to deepen. Left unchecked, these forces will continue to divide the U.S. economy and U.S. society by skill-level, occupation, and economic class – the kind of work people do. And this rising economic divide of work and class will also continue to be reflected in and overlaid by a deepening geographic divide, as the geography of class compounds economic and social inequality. Public policy then will have to focus not just on generating jobs but on improving the content of many of those jobs, especially in the service class, increasing innovation and productivity, more fully utilizing and engaging workers’ capabilities and talents, and improving wages.

My next post will look at the projections for blue-collar factory work. Future posts will cover projections for the growth of lower-skill, lower-pay service work and the projected increase in higher-wage knowledge and creative work.